Tham khảo tài liệu 'the microguide to process modeling in bpmn by mr tom debevoise and rick geneva_11', kỹ thuật - công nghệ, điện - điện tử phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Transformations to Improve Fit In order to see more detail we generate a full size version of the residuals versus predictor variable plot. This plot suggests that the errors now satisfy the assumption of homogeneous variances. NIST SEMATECH HOME tools AIDS Isẽarch BACK NÉXĨ http div898 handbook pmd section6 5 of 5 5 1 2006 10 22 49 AM . Weighting to Improve Fit ENGINEERING STATISTICS HANDBOOK home TOOLS AIDS I SEARCH back next 4. Process Modeling . Case Studies in Process Modeling . Ultrasonic Reference Block Study . Weighting to Improve Fit Weighting Another approach when the assumption of constant variance of the errors is violated is to perform a weighted fit. In a weighted fit we give less weight to the less precise measurements and more weight to more precise measurements when estimating the unknown parameters in the model. Finding An Techniques for determining an appropriate weight function were discussed in detail in Section Appropriate . Weight Fimctkm In this case we have replication in the data so we can fit the power model ln ỡ ln 7lrT hl i-ji to the variances from each set of replicates in the data and use for the weights. z 2 Fit for Estimating Weights Dataplot generated the following output for the fit of ln variances against ln means for the replicate groups. The output has been edited slightly for display. LEAST SQUARES MULTILINEAR FIT SAMPLE SIZE N 22 NUMBER OF VARIABLES 1 PARAMETER ESTIMATES APPROX. ST. DEV. T VALUE 1 A0 11. 2 A1 XTEMP RESIDUAL STANDARD DEVIATION RESIDUAL DEGREES OF FREEDOM 20 http div898 handbook pmd section6 1 of 6 5 1 2006 10 22 53 AM . Weighting to Improve Fit Residual Plot for Weight Function The fit output and plot from the replicate variances against the replicate means shows that the linear fit provides a reasonable fit with an estimated slope of . Based on .
